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The topography of thought.
Jonah Berger1, Olivier Toubia2
1Wharton School, University of Pennsylvania, Philadelphia, PA 19104, USA.
PNAS Nexus
|May 8, 2024
Summary
Students whose college essays explore diverse ideas slowly and deliberately achieve higher college GPAs. This essay topography predicts academic success beyond socioeconomic factors, revealing insights into thought processes.
Area of Science:
- Computational Linguistics
- Educational Psychology
- Cognitive Science
Background:
- Language is fundamental to human expression and cognition.
- Understanding the link between language structure and cognitive abilities is crucial.
- Predicting academic success often relies on traditional metrics, but deeper insights may exist.
Purpose of the Study:
- To investigate if the semantic structure of written language predicts academic success.
- To explore the relationship between essay 'topography' and college grade point average (GPA).
- To develop a novel, objective method for quantifying thought patterns in text.
Main Methods:
- Applied natural language processing (NLP) techniques to analyze over 40,000 college application essays.
- Quantified essay topography by measuring semantic breadth and the pace of semantic shifts.
- Controlled for numerous confounding variables, including SAT scores and parental education.
Main Results:
- Students whose essays covered more semantic ground achieved higher GPAs.
- Slower semantic progression (moving between more similar ideas) correlated with better academic outcomes.
- These findings remained significant even after controlling for socioeconomic and academic predictors.
Conclusions:
- Essay topography, a measure of semantic structure, is a significant predictor of academic success.
- Language use reflects underlying cognitive processes and can offer insights into future performance.
- This NLP-based approach provides a scalable and objective tool for analyzing thought patterns.
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